{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XBLNOKXARE2MYMSAPVMRHHXHJE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"da2235ee445c4c741d0538d57f57520d9da578472cfffa7e8d275cb54877e9e2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-02-10T16:20:49Z","title_canon_sha256":"3cdb48082434bb1b10b47c1847d27af9b472cf1667437f39378fc999be76dc08"},"schema_version":"1.0","source":{"id":"2002.03912","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.03912","created_at":"2026-07-05T00:59:23Z"},{"alias_kind":"arxiv_version","alias_value":"2002.03912v3","created_at":"2026-07-05T00:59:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.03912","created_at":"2026-07-05T00:59:23Z"},{"alias_kind":"pith_short_12","alias_value":"XBLNOKXARE2M","created_at":"2026-07-05T00:59:23Z"},{"alias_kind":"pith_short_16","alias_value":"XBLNOKXARE2MYMSA","created_at":"2026-07-05T00:59:23Z"},{"alias_kind":"pith_short_8","alias_value":"XBLNOKXA","created_at":"2026-07-05T00:59:23Z"}],"graph_snapshots":[{"event_id":"sha256:5be252f90d41cd960cab758f0b371ec1d1a0aa50df60ee25c904e1c4ef657420","target":"graph","created_at":"2026-07-05T00:59:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2002.03912/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a deep generative model for unsupervised text style transfer that unifies previously proposed non-generative techniques. Our probabilistic approach models non-parallel data from two domains as a partially observed parallel corpus. By hypothesizing a parallel latent sequence that generates each observed sequence, our model learns to transform sequences from one domain to another in a completely unsupervised fashion. In contrast with traditional generative sequence models (e.g. the HMM), our model makes few assumptions about the data it generates: it uses a recurrent language model as","authors_text":"Graham Neubig, Junxian He, Taylor Berg-Kirkpatrick, Xinyi Wang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-02-10T16:20:49Z","title":"A Probabilistic Formulation of Unsupervised Text Style Transfer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.03912","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:06d90b3d236e5cb9a9ea8e841050d6808e7363a75ed2d8fbc94f4de40a8fbbb6","target":"record","created_at":"2026-07-05T00:59:23Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"da2235ee445c4c741d0538d57f57520d9da578472cfffa7e8d275cb54877e9e2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-02-10T16:20:49Z","title_canon_sha256":"3cdb48082434bb1b10b47c1847d27af9b472cf1667437f39378fc999be76dc08"},"schema_version":"1.0","source":{"id":"2002.03912","kind":"arxiv","version":3}},"canonical_sha256":"b856d72ae08934cc32407d59139ee749115993442df04bd3c3c74195b58f36ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b856d72ae08934cc32407d59139ee749115993442df04bd3c3c74195b58f36ce","first_computed_at":"2026-07-05T00:59:23.919256Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:59:23.919256Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tvE50m3WNLqAcG30CB2wkXbQJhOulQjPTImG5guXJRgE+NvRASKAtOYfh4kYH5XuqgcW1B8qk3S3ECa5KizDDg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:59:23.919615Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.03912","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:06d90b3d236e5cb9a9ea8e841050d6808e7363a75ed2d8fbc94f4de40a8fbbb6","sha256:5be252f90d41cd960cab758f0b371ec1d1a0aa50df60ee25c904e1c4ef657420"],"state_sha256":"dc131195c74da0d7d949be6a11f1940119691f06d4a680656417dc2dcf2dcfed"}